The PLOS ONE collection on machine learning in health and biomedicine: Towards open code and open data

PLoS ONE

Volumn 14, Issue 1, 2019, Pages

  Celi, Leo A ^a   Citi, Luca ^b   Ghassemi, Marzyeh ^c,d   Pollard, Tom J ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b UNIVERSITY OF ESSEX   (United Kingdom)

^c UNIVERSITY OF TORONTO   (Canada)

^d West Tower   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BIOMEDICINE; HUMAN; MACHINE LEARNING; REPRODUCIBILITY; ALGORITHM; HEALTH CARE DELIVERY; INFORMATION DISSEMINATION; MEDICAL RESEARCH; PEER REVIEW;

ALGORITHMS; BIOMEDICAL RESEARCH; DELIVERY OF HEALTH CARE; HUMANS; INFORMATION DISSEMINATION; MACHINE LEARNING; PEER REVIEW, RESEARCH;

EID: 85060005791     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0210232     Document Type: Article

References (41)

1. National Institutes of Health (NIH). NIH releases strategic plan for data science. Retrieved November 1, 2018, from https://www.nih.gov/news-events/news-releases/nih-releases-strategic-plan-data-science.
2. Kucur ŞS, Holló G, Sznitman R (2018) A deep learning approach to automatic detection of early glaucoma from visual fields. PLOS ONE 13(11): e0206081. https://doi.org/10.1371/journal.pone.0206081PMID: 30485270
3. Steele AJ, Denaxas SC, Shah AD, Hemingway H, Luscombe NM (2018) Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease. PLOS ONE 13(8): e0202344. https://doi.org/10.1371/journal.pone.0202344PMID: 30169498
4. Koitka S, Demircioglu A, Kim MS, Friedrich CM, Nensa F (2018) Ossification area localization in pediatric hand radiographs using deep neural networks for object detection. PLOS ONE 13(11): e0207496. https://doi.org/10.1371/journal.pone.0207496 PMID: 30444906
5. Maggio V, Chierici M, Jurman G, Furlanello C (2018) Distillation of the clinical algorithm improves prognosis by multi-task deep learning in high-risk Neuroblastoma. PLOS ONE 13(12): e0208924. https://doi.org/10.1371/journal.pone.0208924 PMID: 30532223
6. Economist The. (2013, October). Unreliable research: Trouble at the lab. The Economist. Retrieved from http://www.economist.com/node/21588057/print
7. Ioannidis J. P., Greenland S., Hlatky M. A., Khoury M. J., Macleod M. R., Moher D., et al. (2014). Increasing value and reducing waste in research design, conduct, and analysis. Lancet, 383(9912), 166–75. http://dx.doi.org/10.1016/S0140-6736(13)62227-8 PMID: 24411645
8. Ioannidis J. P. (2018) All science should inform policy and regulation. PLoS Med. 2018; 15(5): e1002576. Published 2018 May 3. http://dx.doi.org/10.1371/journal.pmed.1002576 PMID: 29723196
9. Baker M. (2016). Why scientists must share their research code. Nature. http://dx.doi.org/10.1038/nature.2016.20504
10. PLOS. Call for Papers (2018). Retrieved November 1, 2018, from https://blogs.plos.org/speakingofmedicine/2018/03/09/call-for-papers-machine-learning-in-health-and-biomedicine/
11. Savage CJ, Vickers AJ (2009) Empirical study of data sharing by authors publishing in PLOS journals. PLOS One 4: e7078. https://doi.org/10.1371/journal.pone.0007078 PMID: 19763261
12. Stodden V., Seiler J., and Ma Z. PNAS March 13, 2018 115 (11) 2584–2589; https://doi.org/10.1073/pnas.1708290115
13. Stodden V. and Miguez S. (2014) ‘Best Practices for Computational Science: Software Infrastructure and Environments for Reproducible and Extensible Research’, Journal of Open Research Software, 2 (1), p. e21. http://doi.org/10.5334/jors.ay
14. Piccolo S. R., & Frampton M. B. (2016). Tools and techniques for computational reproducibility. Giga-science, 5(1), 30. https://doi.org/10.1186/s13742-016-0135-4 PMID: 27401684
15. Oudeyer P.-Y., & Merrick K. (eds) (2016). CDS Newsletter—The of the Technical Committee on Cognitive and Developmental Systems. Volume 13, number 2, Fall 2016.
16. Alnoamany Y., & Borghi J. A. (2018). Towards computational reproducibility: researcher perspectives on the use and sharing of software (No. e26727v1). PeerJ Preprints. http://dx.doi.org/10.7717/peerj-cs. 163
17. Buckheit J. B., & Donoho D. L. (1995). Wavelab and reproducible research. In Wavelets and statistics (pp. 55–81). Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2544-7_5
18. Torvalds L., & Hamano J. (2010). Git: Fast version control system. Retrieved November 1, 2018, from http://git-scm.com.
19. Code Ocean. Retrieved November 1, 2018, from https://codeocean.com/.
20. Binder. Retrieved November 1, 2018, from https://mybinder.org/
21. The eLife blog: Introducing Binder 2.0. Retrieved November 1, 2018, from https://elifesciences.org/labs/8653a61d/introducing-binder-2-0-share-your-interactive-research-environment
22. Varoquaux G. (2016). Beyond computational reproducibility, let us aim for reusability. Newsletter of the IEEE Technical Committee on Cognitive and Developmental Systems, 13(2).
23. Auffray C., Balling R., Barroso I., Bencze L., Benson M., Bergeron J., et al. (2016). Making sense of big data in health research: towards an EU action plan. Genome medicine, 8(1), 71. https://doi.org/10.1186/s13073-016-0323-y PMID: 27338147
24. Kohane, I. S., Van Wingerde, F. J., Fackler, J. C., Cimino, C., Kilbridge, P., Murphy, S., et al. (1996). Sharing electronic medical records across multiple heterogeneous and competing institutions. In Proceedings of the AMIA Annual Fall Symposium (p. 608). American Medical Informatics Association.
25. Dye C., Bartolomeos K., Moorthy V., & Kieny M. P. (2016). Data sharing in public health emergencies: a call to researchers. Bull World Health Organ, 94(3), 158. https://doi.org/10.2471/BLT.16.170860 PMID: 26966322
26. Margolis R., Derr L., Dunn M., Huerta M., Larkin J., Sheehan J., et al. (2014). The National Institutes of Health’s Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data. Journal of the American Medical Informatics Association, 21(6), 957–958. https://doi.org/10.1136/amiajnl-2014-002974 PMID: 25008006
27. UKRI. Common principles on data policy. Retrieved November 1, 2018, from https://www.ukri.org/funding/information-for-award-holders/data-policy/common-principles-on-data-policy/
28. European Commission. Research & Innovation—Participant Portal H2020 Online Manual. Retrieved November 1, 2018, from http://ec.europa.eu/research/participants/docs/h2020-funding-guide/crosscutting-issues/open-access-data-management/data-management_en.htm
29. Piwowar H (2011) Who shares? Who doesn’t? Factors associated with openly archiving raw research data. PLoS One 6: e18657. https://doi.org/10.1371/journal.pone.0018657 PMID: 21765886
30. Mello MM, Van Lieou BS, Goodman SN (2018) Clinical trials participants’ views on the risks and benefits of data sharing. N Eng J Med 378:2202–2211.
31. Vogeli C, Yucel R, Bendavid E, Jones L, Anderson M, et al. (2006) Data withholding and the next generation of scientists: results of a national survey. Acad Med 81: 128–136. PMID: 16436573
32. Alsheikh-Ali AA, Qureshi W, Al-Mallah MH, Ioannidis J (2011) Public availability of published research data in high-impact journals. PLoS One 6: e24357. https://doi.org/10.1371/journal.pone.0024357PMID: 21915316
33. Campbell EG, Clarridge BR, Gokhale M, Birenbaum L, Hilgartner S, et al. (2002) Data withholding in academic genetics: evidence from a national survey. Jama 287: 473–480. PMID: 11798369
34. Blumenthal D, Campbell EG, Gokhale M, Yucel R, Clarridge B, et al. (2006) Data withholding in genetics and the other life sciences: prevalences and predictors. Acad Med 81: 137–145. https://www.ncbi.nlm.nih.gov/pubmed/16436574 PMID: 16436574
35. Wilkinson Mark D., Dumontier Michel, Aalbersberg IJsbrand Jan, Appleton Gabrielle, Axton Myles, et al. "The FAIR Guiding Principles for scientific data management and stewardship". Scientific Data (2016). https://doi.org/10.1038/sdata.2016.18
36. McLennan S, Shaw D, Celi LA (2018) The challenge of local consent requirements for global critical care databases. https://doi.org/10.1007/s00134-018-5257-y PMID: 29922844
37. Guinchard A. Taking proportionality seriously: The use of contextual integrity for a more informed and transparent analysis in EU data protection law. 23 April 2018. https://onlinelibrary.wiley.com/doi/abs/10.1111/eulj.12273
38. LeVeque R.J. Top Ten Reasons to Not Share Your Code (and why you should anyway). Retrieved November 1, 2018, from https://faculty.washington.edu/rjl/pubs/topten/topten.pdf
39. Barnes N. Publish your computer code: it is good enough. Nature 467, 753 (2010). https://www.nature.com/news/2010/101013/full/467753a.html https://doi.org/10.1038/467753a PMID: 20944687
40. Wittek P. PLOS Blogs: Stop hiding your code. Retrieved November 1, 2018, from https://blogs.plos.org/blog/2018/04/18/stop-hiding-your-code/
41. Eglen SJ, Marwick B, Halchenko YO, Hanke M, Sufi S, Gleeson P, et al. Toward standard practices for sharing computer code and programs in neuroscience. Nature Neuroscience. 2017 May 25; 20(6):770. https://doi.org/10.1038/nn.4550 PMID: 28542156